基于改进Steger算法的线结构光中心提取

Line Structured Light Center Extraction Based on Improved Steger Algorithm

为减小Steger算法提取光条纹中心时,易受环境干扰造成光条纹中心提取精度下降的问题。提出一种改进的Steger算法,该算法使用自适应卷积模板滤波并结合基于大津法的阈值分割,得到线结构光条纹感兴趣区域,然后根据几何中心法快速获取到条纹中心的粗略位置,并根据条纹区域的线宽分段,使用Steger法提取结构光条纹中心线亚像素位置。实验结果表明该算法与灰度重心法和传统Steger法相比,能够准确有效地获取结构光光条中心位置,具有较高的提取精度和良好的稳定性,为结构光三维重建建立了基础。

In order to reduce the problem that the Steger algorithm is susceptible to environmental interference when extracting the center of the light stripe,the accuracy of the center of the light stripe is reduced.An improved Steger algorithm was proposed,which uses adaptive convolutional template filtering combined with threshold segmentation based on the Otsu method to obtain the area of interest of the line structured light stripe,and then the rough position of the stripe center was quickly obtained according to the geometric center method.According to the line width segmentation of the stripe area,the Steger method was used to extract the sub-pixel position of the center line of the structured light stripe.The results show that compared with the gray barycentric method and the traditional Steger method,the experimental results can accurately and effectively obtain the center position of the structured light strip,with higher extraction accuracy and good stability,and establish a foundation for the structured light 3D reconstruction.